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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Histogrammatic Method for Determining Relative Abundance of Input Gas Pulse

To satisfy the Major Constituents Analysis (MCA) requirements for the Vehicle Cabin Atmosphere Monitor (VCAM), this software analyzes the relative abundance ratios for N2, O2, Ar, and CO2 as a function of time and constructs their best-estimate mean. A histogram is first built of all abundance ratios for each of the species vs time. The abundance peaks corresponding to the intended measurement and any obfuscating background are then separated via standard peak-finding techniques in histogram space. A voting scheme is then used to include/exclude this particular time sample in the final average based on its membership to the intended measurement or the background population. This results in a robust and reasonable estimate of the abundance of trace components such as CO2 and Ar even in the presence of obfuscating backgrounds internal to the VCAM device. VCAM can provide a means for monitoring the air within the enclosed environments, such as the ISS (International Space Station), Crew Exploration Vehicle (CEV), a Lunar Habitat, or another vehicle traveling to Mars. Its miniature pre-concentrator, gas chromatograph (GC), and mass spectrometer can provide unbiased detection of a large number of organic species as well as MCA analysis. VCAM s software can identify the concentration of trace chemicals and whether the chemicals are on a targeted list of hazardous compounds. This innovation s performance and reliability on orbit, along with the ground team s assessment of its raw data and analysis results, will validate its technology for future use and development.

Mandrake, Lukas↗
NASA NTRS2018

Introduction to Data Assimilation

Atmospheric data assimilation is a class of techniques used for producing descriptions of fields of air temperature, pressure, humidity, wind, etc. on a spatial grid or in terms of a finite functional representation. These are then used to initialize numerical weather forecasts or to analyze the atmosphere for other purposes. The techniques combine past, present, and even future observations in an approximate statistically optimal way. Various types of statistical or physically-based models and their corresponding adjoints are employed to relate diverse fields in both time and space and to relate what is observed to what is being analyzed. Computationally, the problem is very demanding and onstraining on the techniques that can be employed on a routine basis.

Atmospheric data assimilation↗
NASA NTRS2019

Portable Laser Guided Robotic Metrology System

This paper introduces the new Portable Laser Guided Robotic antenna range (PLGR) at the National Aeronautics and Space Administration's (NASA) Glenn Research Center. Previous work used industrial robots in fixed facilities to characterize antennas and required fixtures that do not lend themselves to portable applications.NASA's PLGR system is designed for in-situ antenna measurements at a remote site. The system consists of a robot arm mounted on a vertical lift and a laser tracker, each on a portable base. The lift and laser tracker enable scanning a surface larger than the robot's reach. To accomplish this the robot first collects all points within its reach, then the system is moved and the laser tracker is used to relocate the robot before additional points are captured.The PLGR architecture will be discussed including how safety systems and path planning are combined to effectively characterize antennas. Software was written in high level languages for flexible integration of vector network analyzers and antenna controllers. Lastly, data will be shown to demonstrate the system functionality and accuracy.

Slater, Peter A.↗
NASA NTRS2019

The Semiannual and 4.4-Year Modulations of Extreme High Tides

In most places extreme high tides undergo a clear seasonal variation. It is well known that semidiurnal tides tend to peak during equinox seasons, and diurnals during solstice seasons. This is a consequence of the solar and lunar declinations, which when large maximize diurnal tides at the expense of semidiurnals. The semiannual range modulation of tidal extremes for a pure semidiurnal tide is determined mainly by the amplitude of the K2 constituent; a pure diurnal is determined mainly by P1. Mixed tidal regimes tend to experience maxima very roughly around the times of solstice, but not always, with the semiannual modulation generally a complicated function of constituent amplitudes and phases. These modulations are here mapped worldwide by analyzing tidal extremes predicted with a global tide model. The known 4.4-year modulation in extreme tides is a consequence of declinational and perigean effects coming in and out of phase. The phase of the 4.4-year modulation is controlled by the phase of the semiannual modulation, irrespective of whether the tide is diurnal, semidiurnal, or mixed.

Ray, R. D.↗
NASA NTRSDate not supplied

TPSAS-NF1676L-16833-DND

Semantic Infrastructure is central to realizing the first goal of the ASDC's Strategic Plan: expanding the ASDC's customer base by improving access to ASDC data. ASDC data comprises a widely heterogeneous set of complex products which presents two significant challenges in data access: Helping customers discover, among many available options, the most suitable data products for their purpose; and Guiding customers to easily and appropriately use products. Data products differ significantly in terms of how the data was collected and processed, even with similar subject matter. Understanding differences is critical to using data effectively. To reach a broader customer range, the ASDC must provide prospective users with enough information to quickly and meaningfully compare and evaluate data products. Data formats and structures also differ among products. Applications displaying and analyzing data need access to federated and semantically disambiguated data. Semantic technologies offer functionality for addressing this issue. Ontologies can provide robust, stable domain models serving as common schema for discovering, evaluating, comparing, and integrating data from disparate products. Reasoning engines and triple stores can leverage ontologies to support intelligent search applications allowing users to discover, query, retrieve, and easily reformat data from a broad spectrum of sources.

Beth Huffer↗
NASA NTRSDate not supplied

From Here to There - Bird's Eye Perspective on Grant Lifecycle and Administration

“What gets measured gets done ”or “measure it to manage it”. The statements have become matter of fact. However, measurement (and even metrics) alone cannot fully communicate an organization’s story without the point of accountability. As a dynamic org, we must measure what is necessary, using the appropriate lenses to analyze the most relevant information that allows robust decision-making. A key function of Program Planning and Control (PP&C) is to assist HRP in the development of such strategy that ensures the proper execution of program research goals. With introspection of the Technical Officer role as defined by 2 CFR(i.e., Part 200, Part 1800)and subsequent governance under the NASA Grant and Cooperative Agreement Manual (GCAM), we’ve realized an obvious disconnect among Principal Investigator’s (PI),technical communication with the elements and some of the administrative/fiduciary requirements that should run parallel to the science work. This find has introduced new program risks as evidenced through incomplete deliverables or other less-than-successful requirements through the lifecycle for work we fund. One solution the Grants Technical Officer proposes is for PP&C to share in the communication with stakeholders of grants administration much earlier in the award process in attempt to reduce programmatic risks; particularly in data, reporting and performance management. As such, the planned IWS 2022 session will focus on(plenary) topics that include (1) definition of the grant lifecycle, (2) anatomy of a grant(NF1687 the award document), and (3)performance measurement/post-award monitoring. As HH&P pursues its strategic objectives to evolve the directorate into a data rich and knowledge rich organization, it has become increasingly important to develop the multiple levels of insight across the program to ensure data and other reporting(qualitative/quantitative), alongside proper administration. And the desired outcome is to make certain HRP meets/exceeds the accountability standard that our research information is received, maintained and accessible in posterity.

Lucy D Barnes-Moten↗
DOE OSTI2019

Real-Time Ice Nuclei Measurements at Oliktok Point Field Campaign Report

The ability of atmospheric particles (aerosols) to serve as heterogeneous ice nuclei (IN) for formation of ice and mixed-phase clouds is one of the least understood microphysical processes resulting in large uncertainties in climate modeling. As stated in the Intergovernmental Panel on Climate Change 2007 report, “The effects of aerosol particles on heterogeneous ice formation are currently insufficiently understood and present another level of challenge for both observations and modeling.” IN can strongly affect cloud radiative properties and precipitation formation. Only a small fraction (often less than 1%) of all aerosol particles act as atmospheric IN. Therefore, it becomes important to identify the active fraction of aerosol particles under a variety of environmental conditions. Proposed IN measurement techniques provide IN concentrations as a function of temperature and humidity conditions, and this unique data set can be analyzed to develop or constrain IN parameterizations that models rely on to calculate primary ice formation. Currently, the processes of ice formation within models are poorly represented, such that climate models often inaccurately partition cloud water between liquid and solid ice. Model studies have shown that uncertainties in cloud phase partitioning induce large uncertainties in the impact of mixedphase clouds on climate change. Arctic clouds composed of ice particles and supercooled liquid droplets at temperatures warmer than -37°C are important for the Arctic’s climate because of their extensive horizontal coverage over long periods, and their impact on the surface radiative balance and thus ice sheet coverage. The complexity of microphysical processes within these clouds and the sensitivity of precipitation to the details of microphysics are not fully understood. In addition, representation of these processes in a variety of cloud models continues to be challenging. Arctic clouds provide unique conditions to understand heterogeneous ice nucleation mechanisms, particularly immersion freezing, and will be the initial focus of the ice nucleation group. The U.S. Department of Energy Atmospheric Radiation Measurement (ARM)-North Slope of Alaska (NSA) site is well equipped with other aerosol measurement (number concentration, size) instruments, and a relationship among long-term IN measurements and aerosol physical and chemical properties under different environmental conditions can be identified and established. The long-term IN measurements will be critical for understanding the ice nucleation process in response to the seasonal variations of aerosol and developing robust ice nucleation parameterizations for cloud and climate models. In the future, IN measurements could also be made at other ARM-NSA sites, specifically, Oliktok Point.

Arctic processes (meteorology), Oliktok Point, aer↗
DOE OSTI2021

Analysis of PNAR Spent Fuel Safeguards Measurements using the ORIGEN Data Analysis Module

This paper summarizes the analysis of the Passive Neutron Albedo Reactivity (PNAR) measurements using the ORIGEN data analysis module for 23 boiling water reactor spent fuel assemblies that were performed in Finland under an international collaboration on spent fuel safeguards verification methods. PNAR is part of the proposed integrated nondestructive system to be used for safeguards verifications at the planned Finnish encapsulation facility. Besides measuring passive neutron and gamma emission rates from an assembly like a Fork detector, PNAR also measures the PNAR ratio, which is expected to correlate with the fissile content in the assembly. The emission rates and PNAR ratio can be used to verify the operator declarations and the fissile content of an assembly, respectively. The analysis was performed using the ORIGEN Data Analysis Module, which was originally developed for predicting Fork detector neutron and gamma signals for spent fuel measurements and has been integrated into the Integrated Review and Analysis Package developed by Euratom and the IAEA. The Module includes the ORIGEN burnup analysis code and integrates detector response functions pre-generated using MCNP to predict detector signals in several seconds per assembly. In this study, new response functions specific to PNAR measurements were generated for ORIGEN Module. The study also analyzes impacts of using detailed fuel design and operation information vs. standard safeguards information on results calculated by ORIGEN Module. Using detailed information reduced the standard deviation of relative differences between calculated and measured neutron count rates among the 23 assemblies from ~10% to ~4%. The results obtained using standard safeguards information for these PNAR measurements were similar to those obtained for the Fork detector. A clear trend was found between the calculated net neutron multiplications and the measured PNAR ratios of the 23 assemblies. This paper describes how ORIGEN Module calculates the expected PNAR neutron and gamma signals and PNAR ratio and how they compare with corresponding measured values.

Ilas, Germina↗
NASA NTRS2001

A Nanometer Aerosol Size Analyzer (nASA) for Rapid Measurement of High-Concentration Size Distributions

We have developed a fast-response Nanometer Aerosol Size Analyzer (nASA) that is capable of scanning 30 size channels between 3 and 100 nm in a total time of 3 seconds. The analyzer includes a bipolar charger (P0210), an extended-length Nanometer Differential Mobility Analyzer (Nano-DMA), and an electrometer (TSI 3068). This combination of components provides particle size spectra at a scan rate of 0.1 second per channel free of uncertainties caused by response-time-induced smearing. The nASA thus offers a fast response for aerosol size distribution measurements in high-concentration conditions and also eliminates the need for applying a de-smearing algorithm to resulting data. In addition, because of its thermodynamically stable means of particle detection, the nASA is useful for applications requiring measurements over a broad range of sample pressures and temperatures. Indeed, experimental transfer functions determined for the extended-length Nano-DMA using the Tandem Differential Mobility Analyzer (TDMA) technique indicate the nASA provides good size resolution at pressures as low as 200 Torr. Also, as was demonstrated in tests to characterize the soot emissions from the J85-GE engine of a T38 aircraft, the broad dynamic concentration range of the nASA makes it particularly suitable for studies of combustion or particle formation processes. Further details of the nASA performance as well as results from calibrations, laboratory tests and field applications are presented.

Han, Hee-Siew↗
DOE OSTI2024

Engineering in Cyber Resilience with Cyber-Informed Engineering

Engineers have super powers to provide cybersecurity resilience with deterministic engineering solutions and to protect systems from the most catastrophic consequences that a cyber saboteur could cause. Come to this session to learn how to use engineering risk management skills to harden your engineered systems from cyberattacks. Objective 1 Identify what system functions could be digitally induced to cause undesired high-impact consequences. Objective 2 Analyze how loss or instability of digital controls in a subsystem could lead to high-impact consequences. Objective 3 Analyze how loss or instability in the digital connectivity between systems could lead to high-impact consequences. Objective 4 Identify engineering controls which could build resilience by eliminating digital loss or instability pathways or reduce the impact of digital loss or instability. This presentation will introduce Cyber-Informed Engineering, described below, and walk participants through specific engineering use cases to show how engineers can consider the potential for cyber sabotage in their existing system designs and enact deterministic engineering-based controls which eliminate pathways for attack or mitigate specific consequences. A wide variety of application use cases will be considered so that audience members can align the material with familiar engineering applications. CIE is an engineering approach that integrates cyber resilience into the conception, design, build, and operation of any physical system that has digital connectivity, sensors, monitoring, or control. CIE offers the opportunity to use engineering to eliminate or mitigate avenues for cyber attack—starting from the earliest stage of design and continuing throughout the system’s lifecycle. Today, engineers and industrial control system (ICS) technicians build engineered systems with specific goals for safety, reliability, and functionality. While systems engineering includes considerable safety and failure mode analysis, cybersecurity risks are often not specifically addressed—particularly the risks of intentional cyber compromise, exploitation, and misuse. Cyber-Informed Engineering pairs well with traditional cyber defenses and offers an extra designed-in protection to eliminate the most catastrophic consequences which can be realized by an adversary should traditional cyber defenses fail.

42 ENGINEERING↗
NASA NTRS1991

Human life support during interplanetary travel and domicile. II - Generic Modular Flow Schematic modeling

This paper describes the Generic Modular Flow Schematic (GMFS) architecture capable of encompassing all functional elements of a physical/chemical life support system (LSS). The GMFS can be implemented to synthesize, model, analyze, and quantitatively compare many configurations of LSSs, from a simple, completely open-loop to a very complex closed-loop. The GMFS model is coded in ASPEN, a state-of-the-art chemical process simulation program, to accurately compute the material, heat, and power flow quantities for every stream in each of the subsystem functional elements (SFEs) in the chosen configuration of a life support system. The GMFS approach integrates the various SFEs and subsystems in a hierarchical and modular fashion facilitating rapid substitutions and reconfiguration of a life support system. The comprehensive ASPEN material and energy balance output is transferred to a systems and technology assessment spreadsheet for rigorous system analysis and trade studies.

Farral, Joseph F.↗
NASA NTRS2006

Immune Response in Microgravity: Genetic Basis and Countermeasure Development Implications

Impairment of the immunity in astronauts and cosmonauts even in shortterm flights is a recognized risk. Longterm orbital space missions and anticipated interplanetary flights increase the concern for more pronounced effects on the immune system with potential clinical consequences. Studies in true and modeled microgravity (MG) have demonstrated that MG directly affects numerous lymphocyte functions. The purpose of this study was to screen for genes involved in lymphocytes response to modeled microgravity (MMG) that could explain the functional and structural changes observed earlier. The microgravity-induced changes in gene expression were analyzed by microarray DNA chip technology. CD3and IL2activated Tcells were cultured in 1g (static) and modeled microgravity (NASA Rotating Wall Vessel bioreactor) conditions for 24 hours. Total RNA was extracted using the RNeasy isolation kit (Qiagen, Valencia, CA). Microarray experiments were performed utilizing Affymetrix Gene Chips (U133A), allowing testing for 18,400 human genes. To decrease the biological variation and aid in detecting microgravity-associated changes, experiments were performed in triplicate using cells obtained from three different donors. Exposure to modeled microgravity resulted in alteration of 89 genes, 10 of which were upregulated and 79 down-regulated. Altered genes were categorized by their function, structural role and by association with metabolic and regulatory pathways. A large proportion was found to be involved in fundamental cellular processes: signal transduction, DNA repair, apoptosis, and multiple metabolic pathways. There was a group of genes directly related to immune and inflammatory responses (IL7R, granulysin, proteasome activator subunit 2, peroxiredoxin 4, HLADRA, lymphocyte antigen 75, IL18R and DOCK2 genes). Among these genes only one (IL7R) was upregulated, the rest were downregulated. The upregulation of the IL7 receptor gene was confirmed by RT PCR. Three genes with altered expression were identified in the apoptosis related group (Granzyme B, APO2 ligand and Beta3endonexin). All of them were downregulated. Gene expression changes in MG might appear pivotal in identifying potential molecular targets for countermeasure development. (Supported by NRA OLMSA02 and NSCORT NAG54072 grants).

Risin, Diana↗
DOE OSTI2023

A Combined Wave Function and Density Functional Approach for K-Edge X-ray Absorption Near-Edge Spectroscopy: A Case Study of Hydrated First-Row Transition Metal Ions

The prediction of X-ray absorption spectra (XAS) of transition metal complexes has important and broad application areas in chemistry and biology. In this letter, we have investigated the predictive ability of multiconfiguration pair-density functional theory (MC-PDFT) for X-ray absorption spectra by calculating the metal K pre-edge features of aquated 3d transition metal ions in common oxidation states. MC-PDFT results were compared with experimentally measured spectra as well as analyzed against results from restricted active-space second-order perturbation theory (RASPT2) and time-dependent density functional theory (TDDFT). As expected, TDDFT performs well for excited states that can be accurately represented by singly excited configurations but fails for excited states where higher order excitations become important. On the other hand, both RASPT2 and MC-PDFT provide quantitatively accurate results for all excited states irrespective of their character. While core-level spectroscopy with RASPT2 is accurate, it is computationally expensive. Finally, our results show that MC-PDFT performs equally well with significantly lower computational cost and is an encouraging alternate approach for X-ray spectroscopies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2005

A Comparison of Geographic Information Systems, Complex Networks, and Other Models for Analyzing Transportation Network Topologies

This report reviews six classes of models that are used for studying transportation network topologies. The report is motivated by two main questions. First, what can the "new science" of complex networks (scale-free, small-world networks) contribute to our understanding of transport network structure, compared to more traditional methods? Second, how can geographic information systems (GIS) contribute to studying transport networks? The report defines terms that can be used to classify different kinds of models by their function, composition, mechanism, spatial and temporal dimensions, certainty, linearity, and resolution. Six broad classes of models for analyzing transport network topologies are then explored: GIS; static graph theory; complex networks; mathematical programming; simulation; and agent-based modeling. Each class of models is defined and classified according to the attributes introduced earlier. The paper identifies some typical types of research questions about network structure that have been addressed by each class of model in the literature.

Alexandrov, Natalia↗
DOE OSTI2021

In-Home Mobility Frequency and Stability in Older Adults Living Alone With or Without MCI: Introduction of New Metrics

Background: Older adults spend a considerable amount of time inside their residences; however, most research investigates out-of-home mobility and its health correlates. We measured indoor mobility using room-to-room transitions, tested their psychometric properties, and correlated indoor mobility with cognitive and functional status. Materials and Methods: Community-dwelling older adults living alone ( n = 139; age = 78.1 ± 8.6 years) from the Oregon Center for Aging & Technology (ORCATECH) and Minority Aging Research Study (MARS) were included in the study. Two indoor mobility features were developed using non-parametric parameters (frequency; stability): Indoor mobility frequency (room-to-room transitions/day) was detected using passive infrared (PIR) motion sensors fixed on the walls in four geographic locations (bathroom; bedroom; kitchen; living room) and using door contact sensors attached to the egress door in the entrance. Indoor mobility stability was estimated by variances of number of room-to-room transitions over a week. Test-retest reliability (Intra-class coefficient, ICC) and the minimal clinically important difference (MCID) defined as the standard error of measurement (SEM) were generated. Generalized estimating equations models related mobility features with mild cognitive impairment (MCI) and functional status (gait speed). Results: An average of 206 days (±127) of sensor data were analyzed per individual. Indoor mobility frequency and stability showed good to excellent test-retest reliability (ICCs = 0.91[0.88–0.94]; 0.59[0.48–0.70]). The MCIDs of mobility frequency and mobility stability were 18 and 0.09, respectively. On average, a higher indoor mobility frequency was associated with faster gait speed (β = 0.53, p = 0.04), suggesting an increase of 5.3 room-to-room transitions per day was associated with an increase of 10 cm/s gait speed. A decrease in mobility stability was associated with MCI (β = −0.04, p = 0.03). Discussion: Mobility frequency and stability in the home are clinically meaningful and reliable features. Pervasive-sensing systems deployed in homes can objectively reveal cognitive and functional status in older adults who live alone.

Wu, Chao-Yi↗
NASA NTRS2018

Behavior of Langmuir Probes in Non-Equilibrium Plasmas

Langmuir probes are diagnostic tools used to determine electron temperature, number density, and plasma potential. Irving Langmuir first used an electrostatic probe in the 1920s to find these characteristics in ionized gases. Single, double, and triple Langmuir probes are commonly used in plasma diagnostics because of their relative simplicity. In the single probe, a swept voltage is applied between the probe tip and circuit common to acquire a waveform showing the collected current as a function of applied voltage. A double Langmuir probe consists of two tips, both inserted into the plasma, with a voltage applied between them. As this voltage is swept, a current-voltage characteristic is measured. In a triple probe three probe tips are electrically coupled to each other with constant non-swept voltages applied between each of the tips. The voltages are selected to represent three points on the single Langmuir probe I-V curve. Elimination of the voltage sweep makes it possible to measure time-varying plasma properties in transient plasmas. Triple Langmuir probe measurements have been widely employed for various types of plasmas, including pulsed and time-varying plasmas such as those seen in pulsed plasma thrusters (PPTs), dense plasma focus devices, plasma flows, and fusion experiments. The typical Langmuir probe analysis for determining electron temperature and number density of the plasma (for a single, double, or triple Langmuir probe) includes an assumption that the plasma is in thermal equilibrium. While the this assumption may be justified for some applications, it is unlikely that it is fully justifiable for pulsed and time-varying plasmas or for the entire time a plasma device is in use. In the present work, we model the responses of Langmuir probes as they are inserted into a range of simple equilibrium and non-equilibrium plasmas. We return to basic governing equations of probe current collection and compute the current to the probes for a distribution function consisting of two Maxwellian distributions with different temperatures (the two-temperature Maxwellian). A variation of this method is also employed, where one of the Maxwellians is offset from zero (in velocity space) to add a suprathermal beam of electrons to the tail of the main Maxwellian distribution (the bump-on-the-tail distribution function). For a range of parameters in these non-Maxwellian distributions, we compute the current collection to the probes. Comparing the distribution function that was assumed a priori with the plasma density and temperature one would infer when applying standard probe theory to analyze the collected currents serves to illustrate the effect a non- Maxwellian plasma would have on results interpreted using the equilibrium probe current collection theory, allowing us to state the magnitudes of these deviations as a function of the assumed distribution function properties.

Polzin, Kurt A.↗
NASA NTRS2003

Characterization of Downstream Ion Energy Distributions From a High Current Hollow Cathode in a Ring Cusp Discharge Chamber

The presence of energetic ions produced by a hollow cathodes operating at high emission currents (greater than 10 Angstroms) has been documented in the literature. As part of an ongoing effort to uncover the underlying physics of the formation of these ions, ion efflux from a high current hollow cathode operating in an ion thruster discharge chamber was investigated. Using a spherical sector electrostatic energy analyzer located downstream of the discharge cathode, the ion energy distribution over a 0 to 60 eV energy range was measured. The sensitivity of the ion energy distribution function to zenith angle was also assessed at 3 different positions: 0, 15, and 25 degrees. The measurements suggest that the majority of the ion current at the measuring point falls into the analyzer with an energy approximately equal to the discharge voltage. The ion distribution, however, was found to be quite broad. The high energy tail of the distribution function tended to grow with increasing discharge current. Sensitivity of the profiles to flow rate at fixed discharge current was also investigated. A simple model is presented that provides a potential mechanism for the production of ions with energies above the discharge voltage.

Foster, John E.↗
DOE OSTI2021

Optimization and supervised machine learning methods for fitting numerical physics models without derivatives

Here, we address the calibration of a computationally expensive nuclear physics model for which derivative information with respect to the fit parameters is not readily available. Of particular interest is the performance of optimization-based training algorithms when dozens, rather than millions or more, of training data are available and when the expense of the model places limitations on the number of concurrent model evaluations that can be performed. As a case study, we consider the Fayans energy density functional model, which has characteristics similar to many model fitting and calibration problems in nuclear physics. We analyze hyperparameter tuning considerations and variability associated with stochastic optimization algorithms and illustrate considerations for tuning in different computational settings.

97 MATHEMATICS AND COMPUTING↗